Optimization Approach for Resource Allocation on Cloud Computing for IoT
Author(s) -
Yeongho Choi,
Yujin Lim
Publication year - 2016
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2016/3479247
Subject(s) - computer science , bidding , cloud computing , combinatorial auction , workload , profit (economics) , service level agreement , quality of service , resource allocation , service provider , distributed computing , operations research , mathematical optimization , service (business) , computer network , operating system , microeconomics , economy , mathematics , engineering , economics
Combinatorial auction is a popular approach for resource allocation in cloud computing. One of the challenges in resource allocation is that QoS Quality of Service constraints are satisfied and provider’s profit is maximized. In order to increase the profit, the penalty cost for SLA Service Level Agreement violations needs to be reduced. We consider execution time constraint as SLA constraint in combinatorial auction system. In the system, we determine winners at each bidding round according to the job’s urgency based on execution time deadline, in order to efficiently allocate resources and reduce the penalty cost. To analyze the performance of our mechanism, we compare the provider’s profit and success rate of job completion with conventional mechanism using real workload data.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom